Featured Publications

  1. M. Brittain, J. Bertram, X. Yang, and P. Wei, Prioritized Sequence Experience Replay, NeurIPS 2019 Workshop on Deep Reinforcement Learning
  2. M. Brittain, X. Yang, and P. Wei, Autonomous Separation Assurance with Deep Multi-Agent Reinforcement Learning. Journal of Aerospace Information Systems,2021: 1-16
  3. M. Brittain and P.Wei, Autonomous Air Traffic Controller: A Deep Multi-Agent Reinforcement Learning Approach, June 2019, ICML 2019 Workshop: RL for Real Life, Long Beach, California

2021

  • M. Brittain, X. Yang, and P. Wei, Autonomous Separation Assurance with Deep Multi-Agent Reinforcement Learning. Journal of Aerospace Information Systems,2021: 1-16
  • W. Guo, M. Brittain, and P. Wei, Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance. Accepted to IEEE Intelligent Transportation Systems Conference, Indianapolis, Indiana
  • A. Weinert, M. Brittain, N. Underhill, and C. Serres, Benchmarking the Process- ing of Aircraft Tracks with Triples Mode and Self-Scheduling. Accepted to IEEE High Performance Extreme Computing, 2021
  • M. Brittain, J. Nagawkar, P. Wei, and L. Leifsson, Multifidelity Aerodynamic Flow Field Prediction Using Conditional Adversarial Networks. AIAA Aviation 2021
  • J. Nagawkar, M. Brittain, and L. Leifsson, Multi fidelity Aerodynamic Flow Field Prediction Using Random Forests. AIAA Aviation 2021
  • M. Brittain and P. Wei, One to Any: Distributed Conflict Resolution with Deep Multi-Agent Reinforcement Learning and Long Short-Term Memory, AIAA 2021-1952. AIAA Scitech 2021 Forum. January 2021

2020

  • M. Brittain and P. Wei, Scalable Autonomous Separation Assurance with Heterogeneous Multi-Agent Reinforcement Learning. Submitted to IEEE Transactions on Automation Science and Engineering, 2020
  • A. Weinert, M. Brittain, and R. Guendel, Frequency of ADS-B Equipped Manned Aircraft Observed by the OpenSky Network, Proceedings 2020, 59, 15., doi:10.3390/proceedings2020059015
  • C. Heisey, M. Brittain, D. Maki, and K. Bush, Multi-Agent Systems Collaborative Teaming (MASCOT) Definition Process to Create Specifications for Multi-Agent System (MAS) Development, November 2020, Accepted to International Command and Control Research and Technology Symposium
  • X. Yang, M. Murphy, M. Brittain and Peng Wei, Computer Vision for Small UAS Onboard Pedestrian Detection, AIAA 2020-3270. AIAA AVIATION 2020 FORUM. June 2020

2019

  • M. Brittain and P. Wei, Autonomous Separation Assurance in A High-Density En-Route Sector: A Deep Multi-Agent Reinforcement Learning Approach, 27-30 October 2019, Accepted to IEEE Intelligent Transportation Systems Conference, Auckland, New Zealand
  • M. Brittain, J. Bertram, X. Yang, and P. Wei, Prioritized Sequence Experience Replay, Accepted to NeurIPS 2019 Workshop on Deep Reinforcement Learning, arXiv preprint arXiv:1905.12726
  • M. Brittain and P.Wei, Autonomous Air Traffic Controller: A Deep Multi-Agent Reinforcement Learning Approach, June 2019, ICML 2019 Workshop: RL for Real Life, Long Beach, California
  • J. Bertram, X. Yang, M. Brittain, and P. Wei, Online Flight Planner with Dynamic Obstacles for Urban Air Mobility, June 2019, AIAA Aviation Conference, Dallas, Texas

2018

  • M. Brittain and P. Wei, Autonomous Sequencing and Separation with Hierarchical Deep Reinforcement Learning, 25-29 June 2018, ICRAT conference, Barcelona, Spain
  • M. Brittain and P. Wei, Towards Autonomous Air Traffic Control for Sequencing and Separation - A Deep Reinforcement Learning Approach, 25-29 June 2018, AIAA Aviation Conference, Atlanta, Georgia
  • M. Brittain and P.Wei, Hierarchical Reinforcement Learning with Deep Nested Agents, 2018 arXiv:1805.07008

List of publications are also available on Google Scholar